def ant_trange(vis):
''' Figure out nominal times for tracking of old EOVSA antennas, and return time
range in CASA format
'''
import eovsa_array as ea
from astropy.time import Time
from taskinit import ms
# Get timerange from the visibility file
# msinfo = dict.fromkeys(['vis', 'scans', 'fieldids', 'btimes', 'btimestr', 'inttimes', 'ras', 'decs', 'observatory'])
ms.open(vis)
# metadata = ms.metadata()
scans = ms.getscansummary()
sk = np.sort(scans.keys())
vistrange = np.array([scans[sk[0]]['0']['BeginTime'],scans[sk[-1]]['0']['EndTime']])
# Get the Sun transit time, based on the date in the vis file name (must have UDByyyymmdd in the name)
aa = ea.eovsa_array()
date = vis.split('UDB')[-1][:8]
slashdate = date[:4] + '/' + date[4:6] + '/' + date[6:8]
aa.date = slashdate
sun = aa.cat['Sun']
mjd_transit = Time(aa.next_transit(sun).datetime(), format='datetime').mjd
# Construct timerange limits based on +/- 3h55m from transit time (when all dishes are nominally tracking)
# and clip the visibility range not to exceed those limits
mjdrange = np.clip(vistrange, mjd_transit - 0.1632, mjd_transit + 0.1632)
trange = Time(mjdrange[0], format='mjd').iso[:19] + '~' + Time(mjdrange[1], format='mjd').iso[:19]
trange = trange.replace('-', '/').replace(' ', '/')
return trange
def amphz(out):
bl2ord = ri.p.bl_list()
uv = copy.copy(out['uvw'][:,:,:2])
time = Time(out['time'],format='jd')
# Get some of the other information we need for this source
srclist = ec.load_VLAcals()
cat = aipy.amp.SrcCatalog(srclist)
aa = ea.eovsa_array()
cat.compute(aa)
aa.cat = cat
src = aa.cat[out['source']]
src.name = out['source']
ha = np.zeros(len(time),'double')
for i in range(1,len(time)):
ha[i] = el.eovsa_ha(src,time[i])
# Select only baselines with Ant 14, and eliminate XY and YX polarizations, and the first time
data = out['x'][bl2ord[:13,13],:2,:,1:]
phz = np.angle(data)
a0 = abs(np.sum(data,3)) # Time averaged amplitude
damp = np.std(abs(data),3)
p0 = np.angle(np.sum(data,3)) # Time averaged angle
nbl,npol,nf,nt = data.shape
pdif = np.zeros(data.shape,'float')
for i in range(nt):
pdif[:,:,:,i] = phz[:,:,:,i] - p0
pdif[np.where(pdif > np.pi)] -= 2*np.pi
pdif[np.where(pdif < -np.pi)] += 2*np.pi
dphase = np.std(pdif,3)
outdict = {'amp':a0,'damp':damp,'phase':p0,'dphase':dphase,'time':time,'ha':np.mean(ha),'dec':src.dec,
'fghz':out['fghz'],'source':src,'uv':uv}
return outdict
def bl_phz(bn,be,fghz,times):
''' Initial test routine to play with baseline corrections. This
routine takes a baseline error in N direction, bn, and baseline
error in E direction, be, as well as a list of frequencies and
times corresponding to an actual observation, and returns the
phase error associated with the baseline error. The phase errors
are relative to the phases at the first time, for easy comparison
with "calibrated" phases in actual data.
Usage:
dphz = bl_phz(bn,be,fghz,times)
'''
nf = len(fghz)
nt = len(times)
aa = ea.eovsa_array()
src = aipy.amp.RadioSpecial('Sun')
dphz = np.zeros((nf,nt),'float')
for i,t in enumerate(times):
aa.set_jultime(t.jd)
src.compute(aa)
ha = el.eovsa_ha(src,t)
dec = src.dec
bx = -bn * np.sin(aa.lat)
by = be
bz = bn*np.cos(aa.lat)
dphz[:,i] = 2*np.pi*(bx*np.cos(dec)*np.cos(ha) - by*np.cos(dec)*np.sin(ha) + bz*np.sin(dec))*fghz/0.3
# Normal phases to first time
blah2 = copy.copy(dphz)
for i in range(nt):
blah2[:,i] = blah2[:,i]-dphz[:,0]
dphz = blah2
# Ensure the phases are between -pi and pi
dphz = dphz % (2*np.pi)
dphz[where(dphz > np.pi)] -= 2*np.pi
return dphz
def ant_trange(vis):
''' Figure out nominal times for tracking of old EOVSA antennas, and return time
range in CASA format
'''
import eovsa_array as ea
from astropy.time import Time
# Get the Sun transit time, based on the date in the vis file name (must have UDByyyymmdd in the name)
aa = ea.eovsa_array()
date = vis.split('UDB')[-1][:8]
slashdate = date[:4] + '/' + date[4:6] + '/' + date[6:8]
aa.date = slashdate
sun = aa.cat['Sun']
mjd_transit = Time(aa.next_transit(sun).datetime(), format='datetime').mjd
# Construct timerange based on +/- 3h55m from transit time (when all dishes are nominally tracking)
trange = Time(mjd_transit - 0.1632, format='mjd').iso[:19] + '~' + Time(mjd_transit + 0.1632, format='mjd').iso[:19]
trange = trange.replace('-', '/').replace(' ', '/')
return trange
def amphz(out):
bl2ord = ri.p.bl_list()
uv = copy.copy(out['uvw'][:, :, :2])
time = Time(out['time'], format='jd')
# Get some of the other information we need for this source
srclist = ec.load_VLAcals()
cat = aipy.amp.SrcCatalog(srclist)
aa = ea.eovsa_array()
cat.compute(aa)
aa.cat = cat
src = aa.cat[out['source']]
src.name = out['source']
ha = np.zeros(len(time), 'double')
for i in range(1, len(time)):
ha[i] = el.eovsa_ha(src, time[i])
# Select only baselines with Ant 14, and eliminate XY and YX polarizations, and the first time
data = out['x'][bl2ord[:13, 13], :2, :, 1:]
phz = np.angle(data)
a0 = abs(np.sum(data, 3)) # Time averaged amplitude
damp = np.std(abs(data), 3)
p0 = np.angle(np.sum(data, 3)) # Time averaged angle
nbl, npol, nf, nt = data.shape
pdif = np.zeros(data.shape, 'float')
for i in range(nt):
pdif[:, :, :, i] = phz[:, :, :, i] - p0
pdif[np.where(pdif > np.pi)] -= 2 * np.pi
pdif[np.where(pdif < -np.pi)] += 2 * np.pi
dphase = np.std(pdif, 3)
outdict = {
'amp': a0,
'damp': damp,
'phase': p0,
'dphase': dphase,
'time': time,
'ha': np.mean(ha),
'dec': src.dec,
'fghz': out['fghz'],
'source': src,
'uv': uv
}
return outdict
def bl_phz(bn, be, fghz, times):
''' Initial test routine to play with baseline corrections. This
routine takes a baseline error in N direction, bn, and baseline
error in E direction, be, as well as a list of frequencies and
times corresponding to an actual observation, and returns the
phase error associated with the baseline error. The phase errors
are relative to the phases at the first time, for easy comparison
with "calibrated" phases in actual data.
Usage:
dphz = bl_phz(bn,be,fghz,times)
'''
nf = len(fghz)
nt = len(times)
aa = ea.eovsa_array()
src = aipy.amp.RadioSpecial('Sun')
dphz = np.zeros((nf, nt), 'float')
for i, t in enumerate(times):
aa.set_jultime(t.jd)
src.compute(aa)
ha = el.eovsa_ha(src, t)
dec = src.dec
bx = -bn * np.sin(aa.lat)
by = be
bz = bn * np.cos(aa.lat)
dphz[:, i] = 2 * np.pi * (bx * np.cos(dec) * np.cos(ha) -
by * np.cos(dec) * np.sin(ha) +
bz * np.sin(dec)) * fghz / 0.3
# Normal phases to first time
blah2 = copy.copy(dphz)
for i in range(nt):
blah2[:, i] = blah2[:, i] - dphz[:, 0]
dphz = blah2
# Ensure the phases are between -pi and pi
dphz = dphz % (2 * np.pi)
dphz[where(dphz > np.pi)] -= 2 * np.pi
return dphz
def src2dict(out):
import aipy
import eovsa_array
import eovsa_cat
import eovsa_lst
import copy
bl2ord = ri.p.bl_list()
uv = copy.copy(out['uvw'][:,:,:2])
time = Time(out['time'],format='jd')
# Get some of the other information we need for this source
srclist = eovsa_cat.load_VLAcals()
cat = aipy.amp.SrcCatalog(srclist)
aa = eovsa_array.eovsa_array()
cat.compute(aa)
aa.cat = cat
src = aa.cat[out['source']]
src.name = out['source']
ha = np.zeros(len(time),'double')
for i in range(len(time)):
ha[i] = eovsa_lst.eovsa_ha(src,time[i])
phase = np.angle(out['x'][bl2ord[:,13]])
outdict = {'phase':phase,'time':time,'ha':ha,'dec':src.dec,'fghz':out['fghz'],'source':src,'uv':uv}
return outdict
